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Glacial lake outburst floods (GLOFs) are among the most concerning consequences of retreating glaciers in mountain ranges worldwide. GLOFs have attracted significant attention amongst scientists and practitioners in the past 2 decades, with particular interest in the physical drivers and mechanisms of GLOF hazard and in socioeconomic and other human-related developments that affect vulnerabilities to GLOF events. This increased research focus on GLOFs is reflected in the gradually increasing number of papers published annually. This study offers an overview of recent GLOF research by analysing 594 peer-reviewed GLOF studies published between 2017 and 2021 (Web of Science and Scopus databases), reviewing the content and geographical focus as well as other characteristics of GLOF studies. This review is complemented with perspectives from the first GLOF conference (7–9 July 2021, online) where a global GLOF research community of major mountain regions gathered to discuss the current state of the art of integrated GLOF research. Therefore, representatives from 17 countries identified and elaborated trends and challenges and proposed possible ways forward to navigate future GLOF research, in four thematic areas: (i) understanding GLOFs – timing and processes; (ii) modelling GLOFs and GLOF process chains; (iii) GLOF risk management, prevention and warning; and (iv) human dimensions of GLOFs and GLOF attribution to climate change. [ABSTRACT FROM AUTHOR]

Annual maxima of daily precipitation sums can be typically described well with a stationary generalized extreme value (GEV) distribution. In many regions of the world, such a description does also work well for monthly maxima for a given month of the year. However, the description of seasonal and interannual variations requires the use of non-stationary models. Therefore, in this paper we propose a non-stationary modeling strategy applied to long time series from rain gauges in Germany. Seasonal variations in the GEV parameters are modeled with a series of harmonic functions and interannual variations with higher-order orthogonal polynomials. By including interactions between the terms, we allow for the seasonal cycle to change with time. Frequently, the shape parameter ξ of the GEV is estimated as a constant value also in otherwise instationary models. Here, we allow for seasonal–interannual variations and find that this is beneficial. A suitable model for each time series is selected with a stepwise forward regression method using the Bayesian information criterion (BIC). A cross-validated verification with the quantile skill score (QSS) and its decomposition reveals a performance gain of seasonally–interannually varying return levels with respect to a model allowing for seasonal variations only. Some evidence can be found that the impact of climate change on extreme precipitation in Germany can be detected, whereas changes are regionally very different. In general, an increase in return levels is more prevalent than a decrease. The median of the extreme precipitation distribution (2-year return level) generally increases during spring and autumn and is shifted to later times in the year; heavy precipitation (100-year return level) rises mainly in summer and occurs earlier in the year. [ABSTRACT FROM AUTHOR]

Flood risk is expected to increase in many regions worldwide due to rapid urbanization and climate change if adequate risk-mitigation (or climate-change-adaptation) measures are not implemented. However, the exact benefits of these measures remain unknown or inadequately quantified for potential future events in some flood-prone areas such as Kathmandu Valley, Nepal, which this paper addresses. This study examines the present (2021) and future (2031) flood risk in Kathmandu Valley, considering two flood occurrence cases (with 100-year and 1000-year mean return periods) and using four residential exposure inventories representing the current urban system (Scenario A) or near-future development trajectories (Scenarios B, C, D) that Kathmandu Valley could experience. The findings reveal substantial mean absolute financial losses (EUR 473 million and 775 million in repair and reconstruction costs) and mean loss ratios (2.8 % and 4.5 %) for the respective flood occurrence cases in current times if the building stock's quality is assumed to have remained the same as in 2011 (Scenario A). Under a "no change" pathway for 2031 (Scenario B), where the vulnerability of the expanding building stock remains the same as in 2011, mean absolute financial losses would increase by 14 %–16 % over those of Scenario A. However, a minimum (0.20 m) elevation of existing residential buildings located in the floodplains and the implementation of flood-hazard-informed land-use planning for 2031 (Scenario C) could decrease the mean absolute financial losses of the flooding occurrences by 9 %–13 % and the corresponding mean loss ratios by 23 %–27 %, relative to those of Scenario A. Moreover, an additional improvement of the building stock's vulnerability that accounts for the multi-hazard-prone nature of the valley (by means of structural retrofitting and building code enforcement) for 2031 (Scenario D) could further decrease the mean loss ratios by 24 %–28 % relative to those of Scenario A. The largest mean loss ratios computed in the four scenarios are consistently associated with populations of the highest incomes, which are largely located in the floodplains. In contrast, the most significant benefits of risk mitigation (i.e., largest reduction in mean absolute financial losses or mean loss ratios between scenarios) are experienced by populations of the lowest incomes. This paper's main findings can inform decision makers about the benefits of investing in forward-looking multi-hazard risk-mitigation efforts. [ABSTRACT FROM AUTHOR]

In this paper future changes of surface water availability in Austria are investigated. We use an ensemble of downscaled and bias-corrected regional climate model simulations of the EURO-CORDEX initiative under moderate mitigation (RCP4.5) and Paris Agreement (RCP2.6) emission scenarios. The climatic water balance and its components (rainfall, snow melt, glacier melt and atmospheric evaporative demand) are used as indicators of surface water availability, and we focus on different altitudinal classes (lowland, mountainous and high alpine) to depict a variety of processes in complex terrain. Apart from analysing the mean changes of these components, we also pursue a hazard risk approach by estimating future changes in return periods of meteorological drought events of a given magnitude as observed in the reference period. The results show, in general, wetter conditions over the course of the 21st century over Austria on an annual basis compared to the reference period 1981–2010 (e.g. RCP4.5 + 107 mm, RCP2.6 + 63 mm for the period 2071–2100). Considering seasonal differences, winter and spring are getting wetter due to an increase in precipitation and a higher fraction of rainfall as a consequence of rising temperatures. In summer only little changes in the mean of the climatic water balance conditions are visible across the model ensemble (e.g. RCP4.5 ±0 mm, RCP2.6 -2 mm for the period 2071–2100). On the contrary, by analysing changes in return periods of drought events, an increasing risk of moderate and extreme drought events during summer is apparent, a signal emerging within the climate system along with increasing warming. [ABSTRACT FROM AUTHOR]

Climate change impact on avalanches is ambiguous. Fewer, wetter, and smaller avalanches are expected in areas where snow cover is declining, while in higher-altitude areas where snowfall prevails, snow avalanches are frequently and spontaneously triggered. In the present paper, we (1) analyse trends in frequency, magnitude, and orientation of wet- and slab-avalanche activity during 59 winter seasons (1962–2021) and (2) detect the main meteorological and snow drivers of wet and slab avalanches for winter seasons from 1979 to 2020 using machine learning techniques – decision trees and random forest – with a tool that can balance the avalanche-day and non-avalanche-day dataset. In terms of avalanches, low to medium–high mountain ranges are neglected in the literature. Therefore we focused on the low-altitude Czech Krkonoše mountain range (Central Europe). The analysis is based on an avalanche dataset of 60 avalanche paths. The number and size of wet avalanches in February and March have increased, which is consistent with the current literature, while the number of slab avalanches has decreased in the last 3 decades. More wet-avalanche releases might be connected to winter season air temperature as it has risen by 1.8 ∘C since 1979. The random forest (RF) results indicate that wet avalanches are influenced by 3 d maximum and minimum air temperature, snow depth, wind speed, wind direction, and rainfall. Slab-avalanche activity is influenced by snow depth, rainfall, new snow, and wind speed. Based on the balanced RF method, air-temperature-related variables for slab avalanches were less important than rain- and snow-related variables. Surprisingly, the RF analysis revealed a less significant than expected relationship between the new-snow sum and slab-avalanche activity. Our analysis allows the use of the identified wet- and slab-avalanche driving variables to be included in the avalanche danger level alerts. Although it cannot replace operational forecasting, machine learning can allow for additional insights for the decision-making process to mitigate avalanche hazard. [ABSTRACT FROM AUTHOR]

Hydro-meteorological risks due to natural hazards such as severe floods, storm surges, landslides and droughts are causing impacts on different sectors of society. Such risks are expected to become worse given projected changes in climate, degradation of ecosystems, population growth and urbanisation. In this respect, nature-based solutions (NBSs) have emerged as effective means to respond to such challenges. A NBS is a term used for innovative solutions that are based on natural processes and ecosystems to solve different types of societal and environmental challenges. The present paper provides a critical review of the literature concerning NBSs for hydro-meteorological risk reduction and identifies current knowledge gaps and future research prospects. There has been a considerable growth of scientific publications on this topic, with a more significant rise taking place from 2007 onwards. Hence, the review process presented in this paper starts by sourcing 1608 articles from Scopus and 1431 articles from the Web of Science. The full analysis was performed on 146 articles. The analysis confirmed that numerous advancements in the area of NBSs have been achieved to date. These solutions have already proven to be valuable in providing sustainable, cost-effective, multi-purpose and flexible means for hydro-meteorological risk reduction. However, there are still many areas where further research and demonstration are needed in order to promote their upscaling and replication and to make them become mainstream solutions. [ABSTRACT FROM AUTHOR]

This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. While there are still large discrepancies between precipitation data sets from observations and models, both show that there is a tendency for moist regions to become wetter and for dry regions to become drier. However, changes in extreme conditions may show the opposite sign to those in average conditions. Where changes in observed intense precipitation have been studied, this has typically been for daily durations or longer. The purpose of this two-part study is to examine daily and sub-daily rainfall extremes for evidence of non-stationarity. Here the problem was addressed by supplementing one long record (Part 1) by a set of shorter records for a 30-yr concurrent period (Part 2). Variations in frequency and magnitude of rainfall extremes across durations from 6 min to 72 h were assessed using data from sites in the south-east of Australia. For the analyses presented in this paper, a peaks-over-threshold approach was chosen since it allows investigating changes in frequency as well as magnitude. Non-parametric approaches were used to assess changes in frequency, magnitude, and quantile estimates as well as the statistical significance of changes for one station (Sydney Observatory Hill) for the period 1921 to 2005. Deviations from the long-term average vary with season, duration, and threshold. The effects of climate variations are most readily detected for the highest thresholds. Deviations from the long-term average tend to be larger for frequencies than for magnitudes, and changes in frequency and magnitude may have opposite signs. Investigations presented in this paper show that variations in frequency and magnitude of events at daily durations are a poor indicator of changes at sub-daily durations. Studies like the one presented here should be undertaken for other regions to allow the identification of regions with significant increase/decrease in intense rainfall, whether there are common features with regards to duration and season exhibiting most significant changes (which in turn could lead to establishing a theoretical framework), and assist in validation of projections of rainfall extremes. [ABSTRACT FROM AUTHOR]

The severe impact of global crises, such as COVID-19 and climate change, is plausibly reshaping the way in which people perceive risks. In this paper, we examine and compare how global crises and local disasters influence public perceptions of multiple hazards in Italy and Sweden. To this end, we integrate information about the occurrence of hazardous events with the results of two nationwide surveys. These included more than 4000 participants and were conducted in two different phases of the COVID-19 pandemic corresponding to low (August 2020) and high (November 2020) levels of infection rates. We found that, in both countries, people are more worried about risks related to experienced events. This is in line with the cognitive process known as the availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind. Epidemics, for example, are perceived as less likely and more impactful in Italy compared to Sweden. This outcome can be explained by cross-country differences in the impact of, as well as governmental responses to, COVID-19. Notwithstanding the ongoing pandemic, people in both Italy and Sweden are highly concerned about climate change, and they rank it as the most likely threat. [ABSTRACT FROM AUTHOR]

The assessment of natural hazards such as floods and droughts is a complex issue that demands integrated approaches and high-quality data. Especially in African developing countries, where information is limited, the assessment of floods and droughts, though an overarching issue that influences economic and social development, is even more challenging. This paper presents an integrated approach to assessing crucial aspects of floods and droughts in the transboundary Mékrou River basin (a portion of the Niger River basin inWest Africa), combining climatic trends analysis and the findings of a household survey. The multivariable trend analysis estimates, at the biophysical level, the climate variability and the occurrence of floods and droughts. These results are coupled with an analysis of household survey data that reveals the behaviour and opinions of local residents regarding the observed climate variability and occurrence of flood and drought events, household mitigation measures, and the impacts of floods and droughts. Based on survey data analysis, the paper provides a per-household cost estimation of floods and droughts that occurred over a 2-year period (2014-2015). Furthermore, two econometric models are set up to identify the factors that influence the costs of floods and droughts to impacted households. [ABSTRACT FROM AUTHOR]

This paper aims to extend and update the survey of extreme wave events in Ireland that was previously carried out by O'Brien et al. (2013). The original catalogue highlighted the frequency of such events dating back as far as the turn of the last ice age and as recent as 2012. Ireland's marine territory extends far beyond its coastline and is one of the largest seabed territories in Europe. It is therefore not surprising that extreme waves have continued to occur regularly since 2012, particularly considering the severity of weather during the winters of 2013-2014 and 2015-2016. In addition, a large number of storm surges have been identified since the publication of the original catalogue. This paper updates the O'Brien et al. (2013) catalogue to include events up to the end of 2017. Storm surges are included as a new category and events are categorised into long waves (tsunamis and storm surges) and short waves (storm and rogue waves). New results prior to 2012 are also included and some of the events previously documented are reclassified. Important questions regarding public safety, services and the influence of climate change are also highlighted. An interactive map has been created to allow the reader to navigate through events: https://drive.google.com/open?id= 19cZ59pDHfDnXKYIziYAVWV6AfoE&usp=sharing. [ABSTRACT FROM AUTHOR]

As an essential component of drought risk, crop–drought vulnerability refers to the degree of the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying drought vulnerability and then identifying its spatial characteristics will help understand vulnerability and develop risk-reduction strategies. We select the European winter wheat growing area as the study area and 0.5 ∘ × 0.5 ∘ grids as the basic assessment units. Winter wheat drought vulnerability curves are established based on the erosion–productivity impact calculator model simulation. Their loss change and loss extent characteristics are quantitatively analysed by the key points and cumulative loss rate, respectively, and are then synthetically identified via K -means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index reaches 0.66. (2) In contrast to the Pod Plain, the stage transitions of the vulnerability curve lags behind in the southern mountain area, indicating a stronger tolerance to drought. (3) According to the loss characteristics during the initial, development, and attenuation stages, the vulnerability curves can be divided into five clusters, namely low-low-low, low-low-medium, medium-medium-medium, high-high-high, and low-medium-high loss types, corresponding to the spatial distribution from low latitude to high latitude and from mountain to plain. The paper provides ideas for the study of the impact of environment on vulnerability and for the possible application of vulnerability curve in the context of climate change. [ABSTRACT FROM AUTHOR]

The twofold aim of this paper is to provide an overview of the current state of resilience research with regard to climate change in the social sciences and propose a research agenda. Resilience research among social scientists is characterized by much more diversity today than a few decades ago. Different definitions and understandings of resilience appear in publications during the last 10 years. Resilience research increasingly bears the mark of social constructivism, a relative newcomer compared to the more long-standing tradition of naturalism. There are also approaches that are indebted to both "naturalism" and "constructivism", which, of course, come in many varieties. Based on our overview of recent scholarship, which is far from being exhaustive, we have identified six research avenues that arguably deserve continued attention. They combine naturalist and constructivist insights and approaches so that human agency, reflexivity, and considerations of justice and equity are incorporated into systems thinking research or supplement such research. Ultimately, we believe that the overarching challenge for future research is to ensure that resilience to climate change does not compromise sustainability and considerations of justice (including environmental, climate, and energy justice). [ABSTRACT FROM AUTHOR]

A number of seaside communities in Troms, northern Norway, are vulnerable to sudden weather-induced access disruptions due to high-impact weather and dependency on one or few roads. In this paper we study changes in winter weather known to potentially cause access disruptions in Troms, for the present climate (1958–2017) and two future periods (2041–2070; 2071–2100). We focus on climate indices associated with snow avalanches and weather that may lead to for example slippery road conditions. In two focus areas, the most important results show larger snow amounts now compared to 50 years ago, and heavy snowfall has become more intense and frequent. This trend is expected to turn in the future, particularly at low elevations where snow cover during winter might become a rarity by 2100. Strong snow drift, due to a combination of snowfall and wind speed, has slightly increased in the two focus areas, but a strong decrease is expected in the future due to less snow. Events of heavy rain during winter are rather infrequent in the present winter climate of Troms, but we show that these events are likely to occur much more often in all regions in the future. [ABSTRACT FROM AUTHOR]

Flooding is one of the main natural hazards in the world and causes huge economic and human impacts. Assessing the flood damage in the Mediterranean region is of great importance, especially because of its large vulnerability to climate change. Most past floods affecting the region were caused by intense precipitation events; thus the analysis of the links between precipitation and flood damage is crucial. The main objective of this paper is to estimate changes in the probability of damaging flood events with global warming of 1.5, 2 and 3 ∘ C above pre-industrial levels and taking into account different socioeconomic scenarios in two western Mediterranean regions, namely Catalonia and the Valencian Community. To do this, we analyse the relationship between heavy precipitation and flood-damage estimates from insurance datasets in those two regions. We consider an ensemble of seven regional climate model (RCM) simulations spanning the period 1976–2100 to evaluate precipitation changes and to drive a logistic model that links precipitation and flood-damage estimates, thus deriving statistics under present and future climates. Furthermore, we incorporate population projections based on five different socioeconomic scenarios. The results show a general increase in the probability of a damaging event for most of the cases and in both regions of study, with larger increments when higher warming is considered. Moreover, this increase is higher when both climate and population change are included. When population is considered, all the periods and models show a clearly higher increase in the probability of damaging events, which is statistically significant for most of the cases. Our findings highlight the need for limiting global warming as much as possible as well as the importance of including variables that consider change in both climate and socioeconomic conditions in the analysis of flood damage. [ABSTRACT FROM AUTHOR]

Classical statistical methods for flood frequency estimation assume stationarity in the gauged data. However, recent focus on climate change and, within UK hydrology, severe floods in 2009 and 2015 has raised the profile of statistical analyses that include trends. This paper considers how parameter estimates for the generalised logistic distribution vary through time in the UK. The UK Benchmark Network (UKBN2) is used to allow focus on climate change separate from the effects of land-use change. We focus on the sensitivity of parameter estimates to adding data, through fixed-width moving window and fixed-start extending window approaches, and on whether parameter trends are more prominent in specific geographical regions. Under stationary assumptions, the addition of new data tends to further the convergence of parameters to some final value. However, addition of a single data point can vastly change non-stationary parameter estimates. Little spatial correlation is seen in the magnitude of trends in peak flow data, potentially due to the spatial clustering of catchments in the UKBN2. In many places, the ratio between the 50-year and 100-year flood is decreasing, whereas the ratio between the 2-year and 30-year flood is increasing, presenting as a flattening of the flood frequency curve. [ABSTRACT FROM AUTHOR]

Dam safety is increasingly subjected to the influence of climate change. Its impacts must be assessed through the integration of the various effects acting on each aspect, considering their interdependencies, rather than just a simple accumulation of separate impacts. This serves as a dam safety management supporting tool to assess the vulnerability of the dam to climate change and to define adaptation strategies under an evolutive dam failure risk management framework. This article presents a comprehensive quantitative assessment of the impacts of climate change on the safety of a Spanish dam under hydrological scenarios, integrating the various projected effects acting on each component of the risk, from the input hydrology to the consequences of the outflow hydrograph. In particular, the results of 21 regional climate models encompassing three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) have been used to calculate the risk evolution of the dam until the end of the 21st century. Results show a progressive deterioration of the dam failure risk, for most of the cases contemplated, especially for the RCP2.6 and RCP4.5 scenarios. Moreover, the individual analysis of each risk component shows that the alteration of the expected inflows has the greater influence on the final risk. The approach followed in this paper can serve as a useful guidebook for dam owners and dam safety practitioners in the analysis of other study cases. [ABSTRACT FROM AUTHOR]

This paper examines the effects of climate change and drought on agricultural incomes in Spanish rural areas. Present research has focused on the effects of these extreme climatological events through response functions, considering effects on crop productivity and average incomes. Among the impacts of droughts, we focused on potential effects on income distribution. The study of the effects on abnormally dry periods is therefore needed in order to perform an analysis of diverse social aspects in the long term. We estimate crop production functions for a range of Mediterranean crops in Spain and we use a measure of the decomposition of inequality to estimate the impact of climate change and drought on yield disparities. Certain adaptation measures may require a better understanding of risks by the public to achieve general acceptance. We provide empirical estimations for the marginal effects of the two impacts considered: farms' average income and income distribution. Our estimates consider crop production response to both biophysical and socioeconomic aspects to analyse long-term implications on competitiveness and disparities. As for the results, we find disparities in the adaptation priorities depending on the crop and the region analysed. [ABSTRACT FROM AUTHOR]

This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: scenario-led (SL), vulnerability-led (VL) and decisioncentric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis of metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation of implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid, showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning. [ABSTRACT FROM AUTHOR]

In addition to storm tides, inland flooding due to intense rainfall has become an increasing threat at coastal lowlands. In particular, the coincidence of both types of events poses great challenges to regional water boards since their technical drainage capacities are limited. In this study, we analysed historical data and scenario-based simulations for gauge Knock near Emden at the German North Sea coast. The evaluation of observed inland flood events shows that mainly moderate storm tide series in combination with large-scale, intense precipitation led to an overload of inland drainage systems, whereas the highest individual storm tides or precipitation events alone could be handled well. Proactive risk management requires climate projections for the future. Therefore, a hydrological and a hydrodynamic ocean model were set up and driven by the same climate simulations to estimate future drainage system overloads. The evaluation of the simulations for the control period of two climate models confirms that the models can reproduce the generation mechanism of the compound events. The coincidence of storm tides and precipitation leads to the highest drainage system overloads, while system overload is also caused by intense rainfall events alone rather than by storm tides without intense precipitation. Scenario projections based on two climate models and two emission scenarios suggest that the intensity of compound events of rainfall and storm tides will increase consistently against the background of mean sea level rise for all investigated climate projections, while simulated system overload is higher for the RCP8.5 scenario compared to the RCP2.6 scenario. Comparable to the past, future compound events will cause more potential damage compared to single extreme events. The model results indicate an increasing frequency and intensity of inland drainage system overloads along the North Sea coast if timely adaptation measures are not taken. [ABSTRACT FROM AUTHOR]

A mega-flood in 1998 caused tremendous losses in China and triggered major policy adjustments in flood-risk management. This paper aims to retrospectively examine these policy adjustments and discuss how China should adapt to newly emerging flood challenges. We show that China suffers annually from floods despite large-scale investments and policy adjustments. Rapid urbanization and climate change will exacerbate future flood risk in China, with cascading impacts on other countries through global trade networks. Therefore, novel flood-risk management approaches are required, such as a risk-based urban planning and coordinated water governance systems with public participation, in addition to traditional structural protection. [ABSTRACT FROM AUTHOR]

Droughts will likely become more frequent, greater in magnitude and longer in duration in the future due to climate change. Already in the present climate, a variety of drought events may occur with different exceedance frequencies. These frequencies are becoming more uncertain due to climate change. Many methods in support of drought risk management focus on providing insight into changing drought frequencies, and use water supply reliability as a key decision criterion. In contrast, robustness analysis focuses on providing insight into the full range of drought events and their impact on a system's functionality. This method has been developed for flood risk systems, but applications on drought risk systems are lacking. This paper aims to develop robustness analysis for drought risk systems, and illustrates the approach through a case study with a water supply reservoir and its users. We explore drought characterization and the assessment of a system's ability to deal with drought events, by quantifying the severity and socioeconomic impact of a variety of drought events, both frequent and rare ones. Furthermore, we show the effect of three common drought management strategies (increasing supply, reducing demand and implementing hedging rules) on the robustness of the coupled water supply and socio-economic system. The case is inspired by Oologah Lake, a multipurpose reservoir in Oklahoma, United States. Results demonstrate that although demand reduction and supply increase may have a comparable effect on the supply reliability, demand reduction may be preferred from a robustness perspective. To prepare drought management plans for dealing with current and future droughts, it is thus recommended to test how alternative drought strategies contribute to a system's robustness rather than relying solely on water reliability as the decision criterion. [ABSTRACT FROM AUTHOR]

In this era of rapid climate change there is an urgent need for interdisciplinary collaboration and understanding in the study of what determines resistance to disasters and recovery speed. This paper is an economist's contribution to that effort. It traces the entrance of the word "resilience" from ecology into the social science literature on disasters, provides a formal economic definition of resilience that can be used in mathematical modeling, incorporates this definition into a multilevel model that suggests appropriate policy roles and targets at each level, and draws on the recent empirical literature on the economics of disaster, searching for policy handles that can stimulate higher resilience. On the whole it provides a framework for simulations and for formulating disaster resilience policies. [ABSTRACT FROM AUTHOR]

The Pátzcuaro–Acambay fault system (PAFS), located in the central part of the Trans-Mexican Volcanic Belt (TMVB), is delimited by an active transtensive deformation area associated with the oblique subduction zone between the Cocos and North American plates, with a convergence speed of 55 mmyr-1 at the latitude of the state of Michoacán, Mexico. Part of the oblique convergence is transferred to this fault system, where the slip rates range from 0.009 to 2.78 mmyr-1. This has caused historic earthquakes in Central Mexico, such as the Acambay quake (Ms=6.9) on 19 November 1912 with surface rupture, and another in Maravatío in 1979 with Ms=5.6. Also, paleoseismic analyses are showing Quaternary movements in some faults, with moderate to large magnitudes. Notably, this zone is seismically active, but lacks a dense local seismic network, and more importantly, its neotectonic movements have received very little attention. The present research encompasses three investigations carried out in the PAFS. First, the estimation of the maximum possible earthquake magnitudes, based on 316 fault lengths mapped on a 15 m digital elevation model, by means of three empirical relationships. In addition, the Hurst exponent Hw and its persistence, estimated for magnitudes Mw (spatial domain) and for 32 slip-rate data (time domain) by the wavelet variance analysis. Finally, the validity of the intrinsic definition of active fault proposed here. The average results for the estimation of the maximum and minimum magnitudes expected for this fault population are 5.5≤Mw≤7. Also, supported by the results of H at the spatial domain, this paper strongly suggests that the PAFS is classified in three different zones (western PAFS, central PAFS, and eastern PAFS) in terms of their roughness (Hw=0.7,Hw=0.5,Hw=0.8 respectively), showing different dynamics in seismotectonic activity and; the time domain, with a strong persistence Hw=0.949 , suggests that the periodicities of slip rates are close in time (process with memory). The fractal capacity dimension (Db) is also estimated for the slip-rate series using the box-counting method. Inverse correlation between Db and low slip-rate concentration was observed. The resulting Db=1.86 is related to a lesser concentration of low slip-rates in the PAFS, suggesting that larger faults accommodate the strain more efficiently (length ≥3 km). Thus, in terms of fractal analysis, we can conclude that these 316 faults are seismically active, because they fulfill the intrinsic definition of active faults for the PAFS. [ABSTRACT FROM AUTHOR]

Small-scale floods are a consequence of high precipitation rates in small areas that can occur along frontal activity and convective storms. This situation is expected to become more severe due to a warming climate, when single precipitation events resulting from deep convection become more intense (super Clausius-Clapeyron effect). Regional climate model (RCM) evaluations and inter-comparisons have shown that there is evidence that an increase in RCM resolution and, in particular, at the convection-permitting scale will lead to a better representation of the spatial and temporal characteristics of heavy precipitation at small and medium scales. In this paper, the benefits of grid size reduction and bias correction in climate models are evaluated in their ability to properly represent flood generation in smalland medium-sized catchments. The climate models are sequentially coupled with a distributed hydrological model. The study area is the Eastern Alps, where small-scale storms often occur along with heterogeneous rainfall distributions leading to a very local flash flood generation. The work is carried out in a small multi-model framework using two different RCMs (CCLM and WRF) in different grid sizes. Bias correction is performed by the use of the novel scaled distribution mapping (SDM), which is similar to the usual quantile mapping (QM) method. The results show that, in the investigated RCM ensemble, no clear added value of the usage of convection-permitting RCMs for the purpose of flood modelling can be found. This is based on the fact that flood events are the consequence of an interplay between the total precipitation amount per event and the temporal distribution of rainfall intensities on a sub-daily scale. The RCM ensemble is lacking in one and/or the other. In the small catchment (< 100 km²), a favourable superposition of the errors leads to seemingly good CCLM 3 km results both for flood statistics and seasonal occurrence. This is, however, not systematic across the catchments. The applied bias correction only corrects total event rainfall amounts in an attempt to reduce systematic errors on a seasonal basis. It does not account for errors in the temporal dynamics and deteriorates the results in the small catchment. Therefore, it cannot be recommended for flood modelling. [ABSTRACT FROM AUTHOR]

Severe tropical cyclone (TC) Debbie made landfall on the northern Queensland coast of Australia on 27 March 2017 after crossing the Great Barrier Reef as a slow-moving Category 4 system. Groups from industry, government and academia collected coastal hazard and impact data before, during and after the event and shared these data to produce a holistic picture of TC Debbie at the coast. Results showed the still water level exceeded the highest astronomical tide by almost a metre. Waves added a further 16% to water levels along the open coast, and were probably unprecedented for this area since monitoring began. In most places, coastal barriers were not breached and as a result there was net offshore sand transport. If landfall had occurred 2 h earlier with the high tide, widespread inundation and overwash would have ensued. This paper provides a case study of effective cross-sector data sharing in a natural hazard context. It advocates for a shared information platform for coastal extremes in Australia to help improve the understanding and prediction of TC-related coastal hazards in the future. [ABSTRACT FROM AUTHOR]

Networks such as transportation, water, and power are critical lifelines for society. Managers plan and execute interventions to guarantee the operational state of their networks under various circumstances, including after the occurrence of (natural) hazard events. Creating an intervention program demands knowing the probable direct and indirect consequences (i.e., risk) of the various hazard events that could occur in order to be able to mitigate their effects. This paper introduces a methodology to support network managers in the quantification of the risk related to their networks. The methodology is centered on the integration of the spatial and temporal attributes of the events that need to be modeled to estimate the risk. Furthermore, the methodology supports the inclusion of the uncertainty of these events and the propagation of these uncertainties throughout the risk modeling. The methodology is implemented through a modular simulation engine that supports the updating and swapping of models according to the needs of network managers. This work demonstrates the usefulness of the methodology and simulation engine through an application to estimate the potential impact of floods and mudflows on a road network located in Switzerland. The application includes the modeling of (i) multiple time-varying hazard events; (ii) their physical and functional effects on network objects (i.e., bridges and road sections); (iii) the functional interrelationships of the affected objects; (iv) the resulting probable consequences in terms of expected costs of restoration, cost of traffic changes, and duration of network disruption; and (v) the restoration of the network. [ABSTRACT FROM AUTHOR]

Vulnerability is a complex concept involving a variety of disciplines from both the physical and socioeconomic sciences. Currently, two opposite trends exist: the physical approach in which vulnerability is analysed as a sum of potential impacts on elements at risk and the social approach in which vulnerability is mostly viewed as a combination of socio-economic variables determining people's ability to anticipate, cope with and recover from a catastrophic event. Finding a way to combine these two approaches is a key issue for a global vulnerability assessment. In this paper we propose to combine elements from these two approaches through the analysis of the potential consequences of a highmagnitude flood event (recurrence interval (RI)>100 years) on human and material stakeholders. To perform our analysis, we choose to upgrade an existing index, the Potential Damage Index (PDI; Puissant et al., 2013), by including social criteria. The PDI was originally developed to assess the physical consequences of hazards on the elements at risk (people, building and lands). It is based on the calculation of three sub-indices representing different types of direct and indirect consequences: physical injury consequences (PIC), structural and functional consequences (SFC), indirect functional consequences (IC). Here, we propose to add a fourth sub-index representing the social consequences. This new sub-index, called social consequences (SC) is obtained by combining criteria derived from INSEE French census data and a risk-perception survey conducted in the field. By combining the four indices (PIC, SFC, IC and SC), we managed to create a new index called the Potential Consequences Index (PCI). The new PCI was tested on the Upper Guil catchment to assess the consequences of a high-magnitude flood event (RI>100 years). Results of the PDI were compared with the PCI and show significant differences. The upgrade to the PDI method provided us with many inputs. The introduction of elements from social vulnerability added an extra dimension to the total consequence map. It allowed us to qualify the potential physical consequences (physical injury, structural and functional consequences) on elements at risk by considering the global resilience of local communities. [ABSTRACT FROM AUTHOR]

Gravel cushions are widely used to absorb the impact energy of falling rocks in open-pit mines. A particularly important application is to enhance the energy-absorbing capacity of rockfall sheds. In this paper, we study how varying the thickness and particle size of a gravel cushion influences its energy-consumption and buffering effects. We performed a series of laboratory drop tests by dropping blocks from a fixed height onto cushions of different thicknesses and particle sizes. The results indicate that, for a given impact energy, the cushion thickness has a strong influence on the measured coefficient of restitution (COR) and therefore impact pressure. Additional tests were performed to study how the radius of the block and the height it is dropped from affect the measured COR. This showed that as the movement height of the block is increased the COR also increases, and blocks with larger radii exhibit a larger variability in measured COR. Finally, we investigated the influence of rockfall block radius, r, movement height, H, cushion thickness, h, and particle size, d, on the COR and the damage depth, L, of the cushion. The test results reveal that the cushion thickness is the primary design parameter, controlling not only COR, but also the stability of the cushion material. The results provide a theoretical and practical basis for the design of gravel cushions for rockfall protection. [ABSTRACT FROM AUTHOR]

The co-occurrence of meteorological, agricultural, and hydrological droughts (multivariate compound droughts) in Switzerland during growing season is problematic due to limitations in water abstractions from rivers during low-flow periods, while at the same time the need for irrigation is high. We analyse compound droughts for 52 catchments in Switzerland during the extended summer season (May–October) using the transient climate and hydrological scenarios for Switzerland (CH2018 and Hydro-CH2018) for both a scenario with mitigation (representative concentration pathway 2.6 (RCP2.6), 8 model chains) and a scenario without mitigation (RCP8.5, 20 model chains). In the RCP8.5 scenario the number of compound drought days is projected to significantly increase by mid-century across all greater regions of Switzerland. The increased frequency is mainly a result of more frequent events (significant) rather than longer event durations (non-significant). Models generally agree on the sign of change. By 2085, compound drought events are projected to occur in median once per catchment per extended summer season north of the Alps and every 1–2 years south of the Alps. Further, the increases in compound drought days mainly occur between May–October, leading to a shift in the main agricultural production season and a more pronounced seasonality with the highest occurrence probabilities between mid-July and the beginning of October. Coupled to the increase in days and events, significantly more catchments are projected to be affected by compound droughts at the same time. In the RCP2.6 (mitigation) scenario, the increase in the number of compound drought days and events is not significant by the end of the 21st century. In comparison with RCP8.5, the number of compound drought days is reduced by 50 %–55 % north of the Alps and by up to 75 % south of the Alps by the end of the century. This emphasizes the need for coordinated adaptation in combination with mitigation measures taken at an early stage. [ABSTRACT FROM AUTHOR]

The possibility of increased landslide activity as a result of climate change has often been suggested, but few studies quantify this connection. Here, we present and utilize a workflow for the first time solely using publicly available data to assess the impact of future changes in landslide dynamic conditioning factors on landslide movement. In our case we apply the workflow to three slow-moving coastal landslides near Vejle, presenting the first study of its kind on Danish landslides. We examine modelled water table depth (WTD) as a dynamic conditioning factor using the DK-HIP model (Danish Hydrological Information and Prognosis system) that simulates historic and future WTD. The data show a clear correlation with landslide movement as recorded by the interferometric synthetic aperture radar (InSAR) time series for the period from 2015 to 2019. Movement of up to 84 mm yr -1 occurs during wet winter months when normalized WTD exceeds +0.5 m. During dry winters, no, or very little, seasonal landslide movement is observed. The DK-HIP model predicts an increase of up to 0.7 m in WTD at the study area by 2100 CE under the RCP8.5 (Representative Concentration Pathway) scenario (95 % confidence), which exceeds the levels this area has experienced in recent decades (mean increase of 0.2 m with a standard deviation of 0.25 m). This is likely to result in increased landslide activity and acceleration of movement. In a previous episode of increased landslide activity linked to extreme precipitation in the early 1980s, one of the examined landslides accelerated, causing damage to infrastructure and buildings. Our study clearly shows that these landslides are sensitive to climate change and highlights the potential of utilizing high-quality, publicly available data to address these complex scientific questions. The quality and quantity of such data are ever increasing, and so is the potential of this kind of approach. [ABSTRACT FROM AUTHOR]

In the current context of global climate change, geohazards such as earthquakes and extreme rainfall pose a serious threat to regional stability. We investigate a three-dimensional (3D) slope dynamic model under earthquake action, derive the calculation of seepage force and the normal stress expression of slip surface under seepage and earthquake, and propose a rigorous overall analysis method to solve the safety factor of slopes subjected to combined with rainfall and earthquake. The accuracy and reliability of the method is verified by two classical examples. Finally, the effects of soil permeability coefficient, porosity, and saturation on slope stability under rainfall in a project located in the Three Gorges Reservoir area are analyzed. The safety evolution of the slope combined with both rainfall and earthquake is also studied. The results indicate that porosity has a greater impact on the safety factor under rainfall conditions, while the influence of permeability coefficient and saturation is relatively small. With the increase of horizontal seismic coefficient, the safety factor of the slope decreases significantly. The influence of earthquake on slope stability is significantly greater than that of rainfall. The corresponding safety factor when the vertical seismic action is vertically downward is smaller than that when it is vertically upward. When considering both horizontal and vertical seismic effects, slope stability is lower. [ABSTRACT FROM AUTHOR]

Winter windstorms are among the most significant natural hazards in Europe linked to fatalities and substantial damage. However, projections of windstorm impact in Europe under climate change are highly uncertain. This study combines climate projections from 30 general circulation models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the climate risk assessment model CLIMADA to obtain projections of windstorm-induced damage over Europe in a changing climate. We conduct an uncertainty–sensitivity analysis and find large uncertainties in the projected changes in the damage, with climate model uncertainty being the dominant factor of uncertainty in the projections. We investigate the spatial patterns of the climate change-induced modifications in windstorm damage and find an increase in the damage in northwestern and northern central Europe and a decrease over the rest of Europe, in agreement with an eastward extension of the North Atlantic storm track into Europe. We combine all 30 available climate models in an ensemble-of-opportunity approach and find evidence for an intensification of future climate windstorm damage, in which damage with return periods of 100 years under current climate conditions becomes damage with return periods of 28 years under future SSP585 climate scenarios. Our findings demonstrate the importance of climate model uncertainty for the CMIP6 projections of windstorms in Europe and emphasize the increasing need for risk mitigation due to extreme weather in the future. [ABSTRACT FROM AUTHOR]

The Mediterranean Basin is one of the regions most affected by climate change, which poses significant challenges to agricultural efficiency and food security. While rising temperatures and decreasing precipitation levels already impose great risks, the effects of compound extreme events (CEEs) can be significantly more severe and amplify the risk. It is therefore of high importance to assess these risks under climate change on a regional level to implement efficient adaption strategies. This study focuses on false-spring events (FSEs), which impose a high risk of crop losses during the beginning of the vegetation growing period, as well as heat–drought compound events (HDCEs) in summer, for a high-impact future scenario (Representative Concentration Pathway (RCP) 8.5). The results for 2070–2099 are compared to 1970–1999. In addition, deviations of the near-surface atmospheric state under FSEs and HDCEs are investigated to improve the predictability of these events. We apply a multivariate, trend-conserving bias correction method (MBCn) accounting for temporal coherency between the inspected variables derived from the European branch of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX). This method proves to be a suitable choice for the assessment of percentile-threshold-based CEEs. The results show a potential increase in frequency of FSEs for large portions of the study domain, especially impacting later stages of the warming period, caused by disproportionate changes in the behavior of warm phases and frost events. Frost events causing FSEs predominantly occur under high-pressure conditions and northerly to easterly wind flow. HDCEs are projected to significantly increase in frequency, intensity, and duration, mostly driven by dry, continental air masses. This intensification is several times higher than that of the univariate components. This study improves our understanding of the unfolding of climate change in the Mediterranean and shows the need for further, locally refined investigations and adaptation strategies. [ABSTRACT FROM AUTHOR]

The paper presents a wavelet transform method to identify possible seismic brightness temperature anomalies that might be associated with the Yushu (Ms = 7.1) earthquake that occurred in Qinghai province of China on 14 April 2010. Daily infrared data from the Chinese geostationary meteorological satellite FY-2E were used for the period from 1 January 2010 to 31 December 2011 and the spatial region 28.1-38.1° N by 91.7-101.7° E. We find that the wavelet transform is an effective method to analyse time series which contain nonstationary power, and identify here anomalous power both in the time and frequency domain. The results show that, over the two years, the relative wavelet power spectrum (RWPS) showed anomalous RWPS variations in nine cases: two of these were followed by earthquakes; seven were not. One of the two RWPS anomalies that were followed by an earthquake was in the southern area of the epicentre of the Yushu earthquake, with the RWPS anomaly starting to appear around 29 March 2010, decreasing in the period before the earthquake, and completely gone by 14 April 2010. The Yushu earthquake was the only strong earthquake within the region and two-year time period chosen, so the abnormal change of RWPS during this time period was possibly associated with the Yushu earthquake. [ABSTRACT FROM AUTHOR]

This paper reports the variation in rainfall characteristics associated with debris flows in the Chenyulan watershed, central Taiwan, between 1963 and 2009. The maximum hourly rainfall Im, the maximum 24 h rainfall Rd, and the rainfall index RI (defined as the product RdIm) were analysed for each rainfall event that triggered a debris flow within the watershed. The corresponding number of debris flows initiated by each rainfall event (N) was also investigated via image analysis and/or field investigation. The relationship between N and RI was analysed. Higher RI of a rainfall event would trigger a larger number of debris flows. This paper also discusses the effects of the Chi-Chi earthquake (CCE) on this relationship and on debris flow initiation. The results showed that the critical RI for debris flow initiation had significant variations and was significantly lower in the years immediately following the CCE of 1999, but appeared to revert to the pre-earthquake condition about five years later. Under the same extreme rainfall event of RI = 365 cm² h-1, the value of N in the CCE-affected period could be six times larger than that in the non-CCE-affected periods. [ABSTRACT FROM AUTHOR]

Disasters are frequent, ongoing and very likely to increase in the future with global climate change. Significant investments in hazard mitigation, policies and emergency management have so far failed to stop disasters. Their recurrences suggest that either there are some gaps in the current response or a different perspective is needed on the way hazards have been dealt with to date. This paper views disasters through the lens of hazardscape, which shows the context of both hazard occurrence and response. It finds that one major cause of response failure is inadequate consideration of the local hazardscape in planning. It notes that although globalization of hazard response practices is progressive, it has been less successful in dealing with local variations in vulnerability. This paper presents the conceptual framework of hazardscape, and illustrates various shortcomings of the current responses in relation to the local hazardscapes where they are adopted. It recommends a holistic approach that considers various aspect of the hazardscape in order to plan a response strategy. [ABSTRACT FROM AUTHOR]

Sea level rise, changes in storms and wave climate as a consequence of global climate change are expected to increase the size and magnitude of flooded and eroding coastal areas, thus having profound impacts on coastal communities and ecosystems. River deltas, beaches, estuaries and lagoons are considered particularly vulnerable to the adverse effects of climate change, which should be studied at the regional/local scale. This paper presents a regional vulnerability assessment (RVA) methodology developed to analyse site-specific spatial information on coastal vulnerability to the envisaged effects of global climate change, and assist coastal communities in operational coastal management and conservation. The main aim of the RVA is to identify key vulnerable receptors (i.e. natural and human ecosystems) in the considered region and localize vulnerable hot spot areas, which could be considered as homogeneous geographic sites for the definition of adaptation strategies. The application of the RVA methodology is based on a heterogeneous subset of bio-geophysical and socio-economic vulnerability indicators (e.g. coastal topography, geomorphology, presence and distribution of vegetation cover, location of artificial protection), which are a measure of the potential harm from a range of climate-related impacts (e.g. sea level rise inundation, storm surge flooding, coastal erosion). Based on a system of numerical weights and scores, the RVA provides relative vulnerability maps that allow to prioritize more vulnerable areas and targets of different climate-related impacts in the examined region and to support the identification of suitable areas for human settlements, infrastructures and economic activities, providing a basis for coastal zoning and land use planning. The implementation, performance and results of the methodology for the coastal area of the North Adriatic Sea (Italy) are fully described in the paper. [ABSTRACT FROM AUTHOR]

Recent EU guidance on adaptation calls for the enhancement of socio-technical resilience to climate change. However, socio-technical resilience is relatively poorly defined and this makes it difficult to apply in practice. This paper uses the concept of identity as a vehicle to advance the definition and assessment of socio-technical resilience. Identity comprises four aspects (components, relationships, innovation, and continuity) that constitute the minimum of what has to be identified and specified if resilience is to be assessed. Characterising the identity of a socio-technical system requires the conceptualisation of these four aspects in relation to the particular function provided by the system (e.g. flood risk management) and also the identification of the specific variables and thresholds that reflect changes in identity. We have demonstrated the utility of the identity approach, using the example of flood risk management for the Island of Dordrecht, the Netherlands. Based on the results, socio-technical resilience has been redefined as the ability of the system to continue to function as expected in the face of change. This definition implies that a system is resilient when it can deliver performance without a change of identity by continuing compliance with standards and expectations. [ABSTRACT FROM AUTHOR]

Although storminess is often cited as a driver of long-term coastal erosion, a lack of suitable datasets has only allowed objective assessment of this claim in a handful of case studies. This reduces our ability to understand and predict how the coastline may respond to an increase in "storminess" as suggested by global and regional climate models. With focus on 16 km of the Sefton coastline bordering the eastern Irish Sea (UK), this paper analyses available measured datasets of water level, surge level, wave height, wind speed and barometric pressure with the objective of finding trends in metocean climate that are consistent with predictions. The paper then examines rates of change in shoreline position over the period 1894 to 2005 with the aim of establishing relationships with climatic variability using a range of measured and modelled metocean parameters (with time spans varying from two to eight decades). With the exception of the mean monthly wind speed, available metocean data do not indicate any statistically significant changes outside seasonal and decadal cycles. No clear relationship was found between changes in metocean conditions and rates of shoreline change along the Sefton coast. High interannual variability and the lack of long-term measurements make unambiguous correlations between climate change and shoreline evolution problematic. However, comparison between the North Atlantic Oscillation winter index (NAOw) and coastline changes suggest increased erosion at times of decreasing NAOw values and reduced erosion at times of increasing NAOw values. Erosion tends to be more pronounced when decreasing NAOw values lead to a strong negative NAO phase. At present, anthropogenic changes in the local sediment budget and the short-term impact of extreme events are still the largest threat likely to affect coastal flooding and erosion risk in the short- and medium-term. Nevertheless, the potential impacts of climate change in the long-term should not be ignored. [ABSTRACT FROM AUTHOR]

The paper introduced the model of the additive tectonics stress from celestial tide-generating force. The model can be used to explain the relationship between additive tectonics stress and seismic fault sliding. According to the periodic changes of the additive tectonics stress, the temperature is analyzes based on the temperature data of NCEP (National Centers for Environmental Prediction) which are gathered for a period of time before and after the Hokkaido, Japan earthquake (25 September 2003). It is found that the abnormal increasing of the temperature is significantly associated with the seismic deformation, even if the epicenter was covered by the clouds. The effect of the additive tectonics stress on activities of the fault is to trigger it at a time when the stress level has already reached an advanced stage as indicated by the temperature increase. Based on this model, it is possible to forewarn short-impending earthquakes. [ABSTRACT FROM AUTHOR]

In January/February 2006, heavy snowfalls in Bavaria (Germany) lead to a series of infrastructural damage of catastrophic nature. Since on many collapsed roofs the total snow load was not exceptional, serious engineering deficiencies in roof construction and a sudden rise in the total snow load were considered to be the trigger of the events. An analysis of the then meteorological conditions reveals, that the early winter of 2005/2006 was characterised by an exceptional continuous snow cover, temperatures remained around the freezing point and no significant snowmelt was evident. The frequent freezing/thawing cycles were followed by a general compaction of the snow load. This resulted in a re-distribution and a new concentration of the snow load on specific locations on roofs. With respect to climate change, the question arises as to whether the risks relating to snow loads will increase. The future probability of a continuous snow cover occurrence with frequent freezing/thawing cycles will probably decline due to predicted higher temperatures. However, where temperatures remain low, an increase in winter precipitation will result in increased snow loads. Furthermore, the variability of extremes is predicted to increase. If heavy snowfall events are more frequent, the risk of a trigger event will likely increase. Finally, an attempt will be made here in this paper to outline a concept for an operational warning system for the Bavarian region. This system envisages to predict the development and risk of critical snow loads for a 3-day time period, utilising a combination of climate and snow modelling data and using this together with a snow pillow devic (located on roofs) and the results of which. [ABSTRACT FROM AUTHOR]

The increasing number and severity of floods, driven by phenomena such as urbanization, deforestation, subsidence and climate change, create a growing need for accurate and timely flood maps. In this paper we present and evaluate a method to create deterministic and probabilistic flood maps from Twitter messages that mention locations of flooding. A deterministic flood map created for the December 2015 flood in the city of York (UK) showed good performance (F(2) = 0.69; a statistic ranging from 0 to 1, with 1 expressing a perfect fit with validation data). The probabilistic flood maps we created showed that, in the York case study, the uncertainty in flood extent was mainly induced by errors in the precise locations of flood observations as derived from Twitter data. Errors in the terrain elevation data or in the parameters of the applied algorithm contributed less to flood extent uncertainty. Although these maps tended to overestimate the actual probability of flooding, they gave a reasonable representation of flood extent uncertainty in the area. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding. [ABSTRACT FROM AUTHOR]

Wildfires have reached an unprecedented scale in the Northern Hemisphere. The summers of 2022 and 2023 demonstrated the destructive power of wildfires, especially in North America and southern Europe. Global warming leads to changes in fire danger. Specifically, fire seasons are assumed to become more extreme and will extend to more temperate regions in northern latitudes in the future. However, the extent to which the seasonality and severity of fire danger in regions of central Europe will change in the future remains to be investigated. Multiple studies claim that natural variability and model uncertainty hide the trend of increasing fire danger in multi-model climate simulations for future potentially fire-prone areas. Such a trend might be isolated with single-model initial-condition large ensembles (SMILEs), which help scientists to distinguish the forced response from natural variability. So far, the SMILE framework has only been applied for fire danger estimation on a global scale. To date, only a few dynamically downscaled regional SMILEs exist, although they enhance the spatial representation of climatic patterns on a regional or local scale. In this study, we use a regional SMILE of the Canadian Regional Climate Model version 5 Large Ensemble (CRCM5-LE) over a region in central Europe under the RCP8.5 (Representative Concentration Pathway) scenario from 1980 to 2099 to analyze changes in fire danger in an area that is currently not fire prone. We use the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. The study area covers four heterogeneous landscapes, namely the Alps, the Alpine Foreland, the lowlands of the South German Escarpment, and the Eastern Mountain Ranges of the Bavarian Forest. We demonstrate that the CRCM5-LE is a dataset suitable for disentangling climate trends from natural variability in a multi-variate fire danger metric. Our results show the strongest increases in the median (50th) and extreme (90th) quantiles of the FWI in the northern parts (South German Escarpment and Eastern Mountain Ranges) of the study area in the summer months of July and August. There, high fire danger becomes the median condition by the end of the century, and levels of high fire danger occur earlier in the fire season. The southern parts (Alps and Alpine Foreland) are less strongly affected by changes in fire danger than the northern parts. However, these regions reach their time of emergence (TOE) in the early 2040s because of very low current fire danger. In the northern parts, the climate change trend exceeds natural variability only in the late 2040s. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by the end of the century. Our results highlight the potential for severe future fire events in central Europe, which is currently not very fire prone, and demonstrate the need for fire management even in regions with a temperate climate. [ABSTRACT FROM AUTHOR]

Flooding associated with Hurricane Maria in 2017 had devastating consequences for lives and livelihoods in Puerto Rico. Yet, an understanding of current and future flood risk on small islands like Puerto Rico is limited. Thus, efforts to build resilience to flooding associated with hurricanes remain constrained. Here, we take an event set of hurricane rainfall estimates from a synthetic hurricane rainfall simulator as the input to an event-based rainfall-driven flood inundation model using the hydrodynamic code LISFLOOD-FP. Validation of our model against high-water-mark data for Hurricane Maria demonstrates the suitability of this model for estimating flood hazard in Puerto Rico. We produce event-based flood hazard and population exposure estimates for the present day and the future under the 1.5 and 2 ∘C Paris Agreement goals. Population exposure to flooding from hurricane rainfall in Puerto Rico for the present-day climate is approximately 8 %–10 % of the current population for a 5-year return period, with an increase in population exposure to flooding by 2 %–15 % and 1 %–20 % under 1.5 and 2 ∘C futures (5-year return period). This research demonstrates the significance of the 1.5 ∘C Paris Agreement goal for Small Island Developing States, providing the first event-based estimates of flooding from hurricane rainfall under climate change for a small island. [ABSTRACT FROM AUTHOR]

Rapid urbanisation, climate change and unsustainable developments are increasing the risk of floods. Flood is a frequent natural hazard that has significant financial consequences for Australia. The emergency response system in Australia is very successful and has saved many lives over the years. However, the preparedness for natural disaster impacts in terms of loss reduction and damage mitigation has been less successful. In this paper, a newly derived flood loss function for Australian residential structures (FLFArs/ has been presented and calibrated by using historic data collected from an extreme event in Queensland, Australia, that occurred in 2013. Afterwards, the performance of the method developed in this work (contrasted to one Australian model and one model from USA) has been compared with the observed damage data collected from a 2012 flood event in Maranoa, Queensland. Based on this analysis, validation of the selected methodologies has been performed in terms of Australian geographical conditions. Results obtained from the new empirically based function (FLFArs/ and the other models indicate that it is apparent that the precision of flood damage models is strongly dependent on selected stage damage curves, and flood damage estimation without model calibration might result in inaccurate predictions of losses. Therefore, it is very important to be aware of the associated uncertainties in flood risk assessment, especially if models have not been calibrated with real damage data. [ABSTRACT FROM AUTHOR]

Many studies discuss the economic and technical aspects of flood warnings. Less attention has been given to the social and behavioural patterns that affect alert services. In particular, the literature focuses on warnings activated in river basins or marine environments without providing clear evidence on Mediterranean coastal areas, even though these are subjected to growing flood risk related to climate change. This paper is a first attempt to bridge this gap. Our research develops an in-depth analysis of the village of Cesenatico on the Adriatic Sea coast. Here the municipality adopted two complementary warning systems: a siren and an alert via short message service (SMS). The analysis focuses on a survey conducted in 2011 and 2012 with 228 participants. The relationships between social and behavioural variables and warning services are investigated as well as flood preparedness and information dissemination. Qualitative evidence from informal interviews is used to support the understanding of key responses. The conclusions show how different social and behavioural patterns can influence the effectiveness and use of warning systems, regardless of the technology adopted and the structural mitigation measures implemented. Education, training and accountability are seen to be critical elements for implementation. Finally, the statistical output is used to suggest new questions and new directions for research. [ABSTRACT FROM AUTHOR]

Total water levels (TWLs), including the contribution of wind waves, associated with tropical cyclones (TCs) are among the most damaging hazards faced by coastal communities. TC-induced economic losses are expected to increase because of stronger TC intensity, sea level rise, and increased populations along the coasts. TC intensity, translation speed, and distance to the coast affect the magnitude and duration of increased TWLs and wind waves. Under climate change, the proportion of high-intensity TCs is projected to increase globally, whereas the variation pattern of TC translation speed also depends on the ocean basin and latitude. There is an urgent need to improve our understanding of the linkages between TC characteristics and TWL components. In the past few years, hurricanes Matthew (2016), Dorian (2019), and Isaias (2020) propagated over the South Atlantic Bight (SAB) with similar paths but resulted in different coastal impacts. We combined in situ observations and numerical simulations with the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to analyze the extreme TWLs under the three TCs. Model verification showed that the TWL components were well reproduced by the present model setup. Our results showed that the peak storm surge and the peak wave runup depended mainly on the TC intensity, the distance to the TC eye, and the TC heading direction. A decrease in TC translation speed primarily led to longer exceedance durations of TWLs, which may result in more severe economic losses. Wave-dependent water level components (i.e., wave setup and wave swash) were found to dominate the peak TWL within the near-TC field. Our results also showed that in specific conditions, the prestorm wave runup associated with the TC-induced swell may lead to TWLs higher than at the peak of the storm. This was the case along the SAB during Hurricane Isaias. Isaias's fast TC translation speed and the fact that its swell was not blocked by any islands were the main factors contributing to these peak TWLs ahead of the storm peak. [ABSTRACT FROM AUTHOR]

Extreme weather events, such as tropical cyclones, often trigger population displacement. The frequency and intensity of tropical cyclones are affected by anthropogenic climate change. However, the effect of historical climate change on displacement risk has so far not been quantified. Here, we show how displacement can be partially attributed to climate change using the example of the 2019 Tropical Cyclone Idai in Mozambique. We estimate the population exposed to high water levels following Idai's landfall using a combination of a 2D hydrodynamical storm surge model and a flood depth estimation algorithm to determine inland flood depths from remote sensing images, factual (climate change) and counterfactual (no climate change) mean sea level, and maximum wind speed conditions. Our main estimates indicate that climate change has increased displacement risk from this event by approximately 12 600–14 900 additional displaced persons, corresponding to about 2.7 % to 3.2 % of the observed displacements. The isolated effect of wind speed intensification is double that of sea level rise. These results are subject to important uncertainties related to both data and modeling assumptions, and we perform multiple sensitivity experiments to assess the range of uncertainty where possible. Besides highlighting the significant effects on humanitarian conditions already imparted by climate change, our study provides a blueprint for event-based displacement attribution. [ABSTRACT FROM AUTHOR]